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CA614 Biometrics

CA614 Biometrics. Welcome Today Admin Module overview Some signals. Admin. Lectures John McKenna, john@computing.dcu.ie Office: 2.47, Tel. (700)5507 Alistair Sutherland, Lecturer Monday 11pm, Q120 Wednesday 9am, X130 Labs Monday 4-6pm, LG.01 Andrew Errity, Tutor

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CA614 Biometrics

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  1. CA614 Biometrics • Welcome • Today • Admin • Module overview • Some signals

  2. Admin • Lectures • John McKenna, john@computing.dcu.ie Office: 2.47, Tel. (700)5507 • Alistair Sutherland, Lecturer • Monday 11pm, Q120 • Wednesday 9am, X130 • Labs • Monday 4-6pm, LG.01 • Andrew Errity, Tutor • Michelle Tooher, Tutor

  3. Admin • Prerequisites • Some maths • probability, linear algebra (matrices), complex numbers • Ability to program • Open mind • Please come see me if you have doubts about prerequisite knowledge

  4. Admin • Assessment • Continuous Assessment: 30% • Assignment: Speaker/Face/Signature Verification • End of module exam: 70% • Books, etc • See Module Descriptor for list • No book purchase necessary • Recommended • Headset required • Composite (with microphone) recommended • Sharing feasible & recommended

  5. What is Biometrics? • “Life measurement” • “ Biometric technologies are automated methods of verifying or recognising the identity of a living person based on a physical or behavioural characteristic”, • Ben Miller, 1987

  6. Projections I Frost & Sullivan (1990)

  7. Projections II IBG Forecast (2000)

  8. Projections III IBIA Forcast (2000)

  9. Module Overview • Module Aims • To cover all modern approaches to biometrics, in the context of automatic computerised methods of identifying an individual based on who they really are - using a variety of attributes such as finger-prints, iris scans etc.

  10. Indicative Syllabus I • Generic mathematical techniques for pattern recognition and digital filtering. • Frequency domain analysis - Fourier and other transforms. • Digital signal processing algorithms. • Benefits of biometrics to identification systems. • Enrolment and template creation. • Accuracy in Biometric systems. False match rates and false non-match rates. • Derived metrics

  11. Indicative Syllabus II • Fingerprint scan. Image acquisition and processing. Competing technologies. Finger scan problems. • Facial scan. Image acquisition and processing. • Iris scan. Image acquisition and processing. • Voice Scan. Speech processing. Implementation of speech processing algorithms. • Other physiological biometrics - signature and key-stroke scanning. • Multifactor identification. • Privacy risks of biometrics.

  12. Learning Outcomes • Awareness of the practicability and applicability of modern method of biometrics. • That an individual's identity can be ascertained to a very high degree of confidence using appropriate sensors and systems. • The common mathematics of pattern recognitionthat underpins this technology. • An understanding of signals: waveforms & spectra • Competence at implementing verification algorithms • Ability to program MATLAB scripts • Ability to use HTK (Hidden Markov Model Toolkit) for verification design

  13. Module Overview • Achieving the aims of the modulewill involve the following: • Communication skills • Group Work skills • Organisational skills • Personal skills • Problem solving skills • Programming skills • Information Technology skills • Cross-disciplinary partnerships • Skills transfer • Module mailing list • Discussion forum; No code!!!

  14. A Taste of Things to Come • Today’s Lab • Speech Waveforms & Spectra • Matlab Intro • Now • Demos • Next • Authentication technologies

  15. Rough Plan • Intro/Background • Maths • Technologies • Issues

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